EP1442453B1 - Frequency-differential encoding of sinusoidal model parameters - Google Patents
Frequency-differential encoding of sinusoidal model parameters Download PDFInfo
- Publication number
- EP1442453B1 EP1442453B1 EP02762729A EP02762729A EP1442453B1 EP 1442453 B1 EP1442453 B1 EP 1442453B1 EP 02762729 A EP02762729 A EP 02762729A EP 02762729 A EP02762729 A EP 02762729A EP 1442453 B1 EP1442453 B1 EP 1442453B1
- Authority
- EP
- European Patent Office
- Prior art keywords
- encoded
- audio signal
- encoding
- directly
- differentially
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Lifetime
Links
Images
Classifications
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
- G10L19/02—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders
Definitions
- This invention relates to a frequency-differential encoding of sinusoidal model parameters.
- model based approaches for low bit-rate audio compression have gained increased interest.
- these parametric schemes decompose the audio waveform into various co-existing signal parts, e.g., a sinusoidal part, a noise-like part, and/or a transient part.
- model parameters describing each signal part are quantized, encoded, and transmitted to a decoder, where the quantized signal parts are synthesised and summed to form a reconstructed signal.
- the sinusoidal part of the audio signal is represented using a sinusoidal model specified by amplitude, frequency, and possibly phase parameters.
- the sinusoidal signal part is perceptually more important than the noise and transient parts, and consequently, a relatively large amount of the total bit budget is assigned for representing the sinusoidal model parameters.
- TD time-differential
- TD encoding While efficient for reducing the bit rate in stationary signal regions, TD encoding is less efficient in regions with abrupt signal changes, since relatively few components can be associated with tonal tracks, and, consequently, a large number of components are encoded directly. Furthermore, to be able to reconstruct a signal from the differential parameters at the decoder, TD encoding is critically dependent on the assumption that the parameters of the previous frame have arrived unharmed. With some transmission channels, e.g. lossy packet networks like the Internet, this assumption may not be valid. Thus, in some cases an alternative to TD encoding is desirable.
- FD frequency-differential
- FD encoding differences between parameters belonging to the same signal frame are quantized and encoded, thus eliminating the dependence on parameters from previous frames.
- FD encoding is well-known in sinusoidal based speech coding, and has recently been used for audio coding as well.
- sinusoidal components within a frame are quantized and encoded in increasing frequency order; first, the component with lowest frequency is encoded directly, and then higher frequency components are quantized and encoded one at a time relative to their nearest lower-frequency neighbour. While this approach is simple, it may not be optimal. For example, in some frames it may be more efficient to relax the nearest-neighbour constraint.
- the inventors have sought to derive a more general method for FD encoding of sinusoidal model parameters.
- the proposed method finds the optimal combination of frequency differential and direct encoding of the sinusoidal components in a frame.
- the method is more general than existing schemes in the sense that it allows for parameter differences involving any component pair, that is to say, not necessarily frequency domain neighbours.
- several (in the extreme case, all) components may be encoded directly, if this turns out to be most efficient.
- the invention is defined by a coding method claim 1, a decoding method claim 11, an encoding device claim 10, a decoding device claim 13, an encoded signal claim 14, a storage medium with an encoded signal claim 15. Preferred embodiments as set forth in the dependent claims.
- Embodiments of the invention can be constituted in a system for transmitting audio signals over an unreliable communication link, such as the Internet.
- a system shown diagrammatically in Figure 8, typically comprises a source of audio signals 10, and transmitting apparatus 12 for transmitting audio signals from the source 10.
- the transmitting apparatus 12 includes an input unit 20 for obtaining an audio signal from the source 10, an encoding device 22 for coding the audio signal to obtain the encoded audio signal, and an output unit 24 for transmitting or recording the encoded audio signal by applying the encoded signal to a network link 26.
- Receiving apparatus 30 connected to the network link 26 to receive the encoded audio signal.
- the receiving apparatus 30 includes an input unit 32 for receiving the encoded audio signal, a device 34 for decoding the encoded audio signal to obtain a decoded audio signal, and an output unit 36 for outputting the decoded audio signal.
- the output signal can then be reproduced, recorded or otherwise processed as required by suitable apparatus 40.
- the signal is encoded in accordance with a coding method comprising a step of encoding parameters of a given sinusoidal component either differentially relative to other components in the same frame or directly, i.e. without differential encoding.
- the method must determine whether or not to use differential coding at any stage in the encoding process.
- the set of all possible combinations of direct and differential quantization is represented using a directed graph (digraph) D as illustrated in Fig. 1.
- the vertex s 0 is a dummy vertex introduced to represent the possibility of direct quantization.
- the edge between s 0 and s 2 represents direct quantization of the parameters of s 2 .
- Each edge is assigned a weight w ij , which corresponds to a cost in terms of rate and distortion of choosing the particular quantization represented by the edge.
- the basic task is to find a rate-distortion optimal combination of direct and differential encoding. This corresponds to finding the subset of K edges in D with minimum total cost, such that each vertex s 1 , ... ,s K has exactly one in-edge assigned.
- r ij and d ij are the rate (i.e. the numbers of bits) and the distortion, respectively, associated with this particular quantization
- ⁇ is a Lagrange multiplier
- column 1 lists output levels for direct amplitude quantizers
- column 2 lists output levels for differential amplitude quantizers
- column 3 lists the set of reachable amplitude levels after differential quantization.
- the values of r ( ⁇ ) are found as entries in pre-calculated Huffman code-word tables.
- Constraint a) is essential since it ensures that each of the K sinusoidal components is quantized and encoded exactly once.
- Constraint b) enforces a particular simple structure on the K edge solution tree. This is of importance for reducing the amount of side information needed to tell the decoder how to combine the transmitted (delta-) amplitudes and frequencies.
- Fig. 3 shows examples of possible solution trees satisfying constraints a) and b). Note that the 'standard' FD encoding configuration used in e.g. some prior art proposals is a special case in Fig. 3c of the presented framework.
- Algorithm 1 is mathematically optimal, while Algorithm 2 provides an approximate solution at a lower computational cost.
- Algorithm 1 In order to solve Problem 1, we reformulate it as a so-called assignment problem, which is a well-known problem in graph-theory. Using the digraph D (Fig. 1), we construct a graph G as shown in Fig. 4. The vertices of G can be divided into two subsets: the subset X on the left-hand side, which contains the vertices s 1 , ... ,s K-1 and K copies of s 0 , and the subset Y on the right-hand side, which contains the vertices s 1 , ... , s K and K -1 dummy vertices, shown as ⁇ .
- edges connect the vertices of X and Y .
- Edges connected to vertices in X correspond to out-edges in the digraph D
- edges connected to vertices s 1 ,...,s K ⁇ Y correspond to in-edges in D .
- the edge from s 2 ⁇ X to s 4 ⁇ Y in G corresponds to the edge s 2 s 4 in the digraph D .
- the solid line edges in graph G represent the 'differential encoding' edges in digraph D .
- each set of K edges in D that satisfies constraints a) and b) of Problem 1 can be represented as an assignment in G of the vertices in X to the vertices in Y , i.e., a subset of 2 K -1 edges in G such that each vertex is assigned exactly one edge.
- Figs. 5a-c show examples of assignments corresponding to the trees in Figs. 3a-c, respectively.
- Problem 1 can be reformulated as the so-called Assignment Problem, which we will refer to as Problem 2.
- Algorithm 1 consists of the following steps. First, the digraph D (and as a result the graph G ) is constructed. Then, the assignment in G with minimal weight (Problem 2) is determined. Finally, from the assignment in G , the optimal combination of direct and differential coding is easily derived.
- Algorithm 2 is an iterative, greedy algorithm that treats the vertices s 1 , ... , s K of the graph D one at a time for increasing indices.
- one of the in-edges of vertex s k is selected from a candidate edge set.
- the candidate set consists of the in-edges of s k originating from vertices with no previously selected out-edge, and the direct encoding edge s 0 s k . From this set, the edge with minimal weight is selected.
- a set of K edges is obtained that satisfies constraints a) and b) of Problem 1.
- this greedy approach is not optimal, i.e., there may exist another set of K edges with a lower total weight satisfying constraints a) and b).
- Algorithm 2 has a computational complexity of O( K 2 ).
- an encoded signal embodying the invention must include side information that describes how to combine the parameters at the decoder.
- side information One possibility is to assign to each possible solution tree one symbol in the side information alphabet.
- K 25 sinusoidal components in a frame, it can be shown that the number of different solution trees is approximately 10 18 , corresponding to 62 bits for indexing the solution tree in the side information alphabet.
- this number is excessive for most applications.
- the side information alphabet only needs to represent topologically distinct solution trees, provided that a particular ordering is applied to the (delta-) parameter sequence.
- topologically distinct trees and parameter ordering
- the spanning trees in Figs. 6a and 6b are topologically identical, since they each consist of a three-edge and a two-edge branch, and would thus be represented with the same symbol in the side information alphabet.
- the tree in Fig. 6c which consists of a single five-edge branch; is topologically distinct from the others. Knowing the topological tree structure and assuming for example that the (delta-) parameters occur branch-wise in the parameter stream with longest branches first, it is possible for the decoder to combine the received parameters correctly.
- preferred embodiments of the invention provide a side information alphabet whose symbols correspond to topologically distinct solution trees.
- An upper bound for the side information is given by the number of such trees.
- Fig. 8 shows the number of topologically distinct trees as a function of the number K of sinusoidal components.
- the graph represents an upper bound for the side information; exploiting statistical properties using e.g. entropy coding may reduce the side information rate further.
- bit rate R Pars needed for encoding of (delta-) amplitudes and frequencies was estimated (using first-order entropies). Furthermore, since Algorithms 1 and 2 require that information about the solution tree structure be sent to the decoder, the bit rate R S.I : needed for representing this side information was estimated as well. Table 1 below shows the estimated bit rates for the various coding strategies and test signals. In this context, comparison of bit rates is reasonable because similar quantizers are used for all experiments, and, consequently, the test signals are encoded at the same distortion level.
- the columns in Table 1 below show bit rates [kbps] for various coding schemes and test signals.
- the table columns are R Pars : bit rate for representing (delta-) amplitudes and frequencies, R S.I : rate needed for side information (tree structures), and R Total : total rate.
- Gain is the relative improvement with various FD encoding schemes over direct encoding (non-differential).
- Table 1 shows that using Algorithm 1 for determining the combination of direct and FD encoding gives a bit-rate reduction in the range of 18.8-27.0% relative to direct encoding.
- Algorithm 2 performs nearly as well with bit-rate reductions in the range of 18.5-26.7%.
- the slightly lower side information resulting from Algorithm 2 is due to the fact that Algorithm 2 tends to produce solution trees with fewer but longer 'branches', thereby reducing the number of different solution trees observed.
- the 'standard' method of FD encoding reduces the bit rate with 12.7-24.0%.
- encoding methods are provided that use two algorithms for determining the bit-rate optimal combination of direct and FD encoding of sinusoidal components in a given frame.
- the presented algorithms showed bit-rate reductions of up to 27% relative to direct encoding.
- the proposed methods reduced the bit rate with up to 7% compared to a typically used FD encoding scheme. While consideration of the invention has been focussed on FD encoding as a stand-alone technique, in further embodiments the scheme is generalizes to describe FD encoding in combination with TD encoding. With such joint TD/FD encoding schemes, it is possible to provide embodiments that combine the strengths of the two encoding techniques.
Abstract
Description
- This invention relates to a frequency-differential encoding of sinusoidal model parameters.
- In recent years, model based approaches for low bit-rate audio compression have gained increased interest. Typically, these parametric schemes decompose the audio waveform into various co-existing signal parts, e.g., a sinusoidal part, a noise-like part, and/or a transient part. Subsequently, model parameters describing each signal part are quantized, encoded, and transmitted to a decoder, where the quantized signal parts are synthesised and summed to form a reconstructed signal. Often, the sinusoidal part of the audio signal is represented using a sinusoidal model specified by amplitude, frequency, and possibly phase parameters. For most audio signals, the sinusoidal signal part is perceptually more important than the noise and transient parts, and consequently, a relatively large amount of the total bit budget is assigned for representing the sinusoidal model parameters. For example, in a known scalable audio coder described by T. S. Verma and T. H. Y. Meng in "A 6kbps to 85kbps scalable audio coder" Proc. IEEE Inst. Conf. Acoust., Speech Signal Processing, Pages 877-880, 2000, more than 70% of the available bits are used for representing sinusoidal parameters.
- Usually, in order to reduce the bit rate needed for the sinusoidal model, interframe correlation between sinusoidal parameters is exploited using time-differential (TD) encoding schemes. An example of such method is disclosed in the document J. Jensens et al. "Optimal time differential encoding of sinusoidal parameters", 22nd Symposium on information theory in the Benelux, May 2001. Sinusoidal components in a current signal frame are associated with quantized components in the previous frame (thus forming 'tonal tracks' in the time-frequency plane), and the parameter differences are quantized and encoded. Components in the current frame that cannot be linked to past components are considered as start-ups of new tracks and are usually encoded directly, with no differential encoding. While efficient for reducing the bit rate in stationary signal regions, TD encoding is less efficient in regions with abrupt signal changes, since relatively few components can be associated with tonal tracks, and, consequently, a large number of components are encoded directly. Furthermore, to be able to reconstruct a signal from the differential parameters at the decoder, TD encoding is critically dependent on the assumption that the parameters of the previous frame have arrived unharmed. With some transmission channels, e.g. lossy packet networks like the Internet, this assumption may not be valid. Thus, in some cases an alternative to TD encoding is desirable.
- One such alternative is frequency-differential (FD) encoding, where intraframe correlation between sinusoidal components is exploited. In FD encoding, differences between parameters belonging to the same signal frame are quantized and encoded, thus eliminating the dependence on parameters from previous frames. FD encoding is well-known in sinusoidal based speech coding, and has recently been used for audio coding as well. Typically, sinusoidal components within a frame are quantized and encoded in increasing frequency order; first, the component with lowest frequency is encoded directly, and then higher frequency components are quantized and encoded one at a time relative to their nearest lower-frequency neighbour. While this approach is simple, it may not be optimal. For example, in some frames it may be more efficient to relax the nearest-neighbour constraint.
- In arriving at the present invention, the inventors have sought to derive a more general method for FD encoding of sinusoidal model parameters. For given parameter quantizers and code-word lengths (in bits) corresponding to each quantization level, the proposed method finds the optimal combination of frequency differential and direct encoding of the sinusoidal components in a frame. The method is more general than existing schemes in the sense that it allows for parameter differences involving any component pair, that is to say, not necessarily frequency domain neighbours. Furthermore, unlike the simple scheme described above, several (in the extreme case, all) components may be encoded directly, if this turns out to be most efficient.
- The invention is defined by a
coding method claim 1, adecoding method claim 11, anencoding device claim 10, adecoding device claim 13, an encoded signal claim 14, a storage medium with an encodedsignal claim 15. Preferred embodiments as set forth in the dependent claims. - Embodiments of the invention will now be described in detail, by way of example, and with reference to the accompanying drawings, in which:
- Figure 1 is a directed graph D used for representing all possible combinations of direct and frequency-differential encoding of the sinusoidal components (K=5) in a given frame;
- Figure 2 shows an example of output levels for scalar amplitude quantizers in an embodiment of the invention;
- Figure 3 shown examples of allowed solution trees for the K = 5 case;
- Figure 4 shows a graph G (K = 5) for representing possible solutions of Problem 1 (as defined below) as assignments, wherein, for clarity, only a few of the edges and weights are shown;
- Figure 5 shows assignments in graph G corresponding to the trees in Fig.3;
- Figures 6a to 6c show examples of topologically identical and distinct solution trees;
- Figure 7 is a graph of the number of topologically distinct solution trees in an encoded signal embodying the invention as a function of the number of sinusoidal components K; and
- Figure 8 is a simplified block diagram of a system for transmitting audio data embodying the invention.
- Embodiments of the invention can be constituted in a system for transmitting audio signals over an unreliable communication link, such as the Internet. Such a system, shown diagrammatically in Figure 8, typically comprises a source of
audio signals 10, and transmittingapparatus 12 for transmitting audio signals from thesource 10. Thetransmitting apparatus 12 includes aninput unit 20 for obtaining an audio signal from thesource 10, anencoding device 22 for coding the audio signal to obtain the encoded audio signal, and anoutput unit 24 for transmitting or recording the encoded audio signal by applying the encoded signal to anetwork link 26. Receivingapparatus 30 connected to thenetwork link 26 to receive the encoded audio signal. Thereceiving apparatus 30 includes aninput unit 32 for receiving the encoded audio signal, adevice 34 for decoding the encoded audio signal to obtain a decoded audio signal, and anoutput unit 36 for outputting the decoded audio signal. The output signal can then be reproduced, recorded or otherwise processed as required bysuitable apparatus 40. - Within the
encoding device 22, the signal is encoded in accordance with a coding method comprising a step of encoding parameters of a given sinusoidal component either differentially relative to other components in the same frame or directly, i.e. without differential encoding. The method must determine whether or not to use differential coding at any stage in the encoding process. - In order to formulate the problem that must be solved by the method to arrive at this determination, consider the situation where a number of sinusoidal components s 1 , ... ,s K have been estimated in a signal frame. Each component s k is described by an amplitude a k and a frequency value ω k . For the purposes of the present description it is not necessary to consider phase values since these may be derived from the frequency parameters or quantized directly. Nonetheless, it will be seen that the invention may in fact be extended to phase values and/or other values such as damping coefficients.
- Consider the following possibilities for quantization of the parameters of a given component:
- 1) Direct quantization (i.e., non-differential), or
- 2) Differential quantization relative to the quantized parameters of one the components at lower frequencies.
- The set of all possible combinations of direct and differential quantization is represented using a directed graph (digraph) D as illustrated in Fig. 1.
- The vertices s 1 , ... ,s K represent the sinusoidal components to be quantized. Edges between these vertices represent the possibilities for differential encoding, e.g., the edge between s 1 and s 4 represents quantization of the parameters of s 4 relative to s 1 (that is, â 4 = â 1 + Δâ 14 for amplitude parameters). The vertex s 0 is a dummy vertex introduced to represent the possibility of direct quantization. For example, the edge between s 0 and s 2 represents direct quantization of the parameters of s 2 . Each edge is assigned a weight w ij , which corresponds to a cost in terms of rate and distortion of choosing the particular quantization represented by the edge. The basic task is to find a rate-distortion optimal combination of direct and differential encoding. This corresponds to finding the subset of K edges in D with minimum total cost, such that each vertex s 1 , ... ,s K has exactly one in-edge assigned.
- The calculation of edge weights will now be described. In principle, each edge weight is of the form:
where r ij and d ij are the rate (i.e. the numbers of bits) and the distortion, respectively, associated with this particular quantization, and λ is a Lagrange multiplier. Generally, since higher-indexed components s j are quantized relative to (already quantized) lower-indexed components as shown in Fig. 1, the exact value of a weight w ij depends on the particular quantization of the lower-indexed component s i . In other words, the value of w ij cannot be calculated before s i has been quantized. To eliminate this dependency, we assume that similar quantizers are used for direct and differential quantization as illustrated in Fig. 2 for amplitude parameters. - In Figure 2,
column 1 lists output levels for direct amplitude quantizers,column 2 lists output levels for differential amplitude quantizers, andcolumn 3 lists the set of reachable amplitude levels after differential quantization. - With this assumption, the quantizer levels that can be reached through direct and differential quantization are identical, and a given component will be quantized in the same way, independent of whether direct or differential quantization is used. This in turn means that the total distortion is constant for any combination of direct and differential encoding, and we can set λ = 0 in
equation 1. Furthermore, now all weight values of D can be calculated in advance as w ij = r ij , where
and the integer r (·) denotes the number of bits needed to represent the quantized parameter (·). In this example, the values of r (·) are found as entries in pre-calculated Huffman code-word tables. - In order to clearly understand the example, it is necessary to formulate the problem that is being addressed. Assuming that the signal frame in question contains K sinusoidal components to be encoded, we formulate the optimal FD encoding problem as follows:
-
- a) each vertex s 1 , ... , s K is assigned exactly one in-edge, and
- b) each vertex s 1 , s K is assigned a maximum of one out-edge.
- Constraint a) is essential since it ensures that each of the K sinusoidal components is quantized and encoded exactly once. Constraint b) enforces a particular simple structure on the K edge solution tree. This is of importance for reducing the amount of side information needed to tell the decoder how to combine the transmitted (delta-) amplitudes and frequencies. Fig. 3 shows examples of possible solution trees satisfying constraints a) and b). Note that the 'standard' FD encoding configuration used in e.g. some prior art proposals is a special case in Fig. 3c of the presented framework.
- In solving the above problem, two algorithms (referred to as
Algorithm 1 and Algorithm 2) are provided.Algorithm 1 is mathematically optimal, whileAlgorithm 2 provides an approximate solution at a lower computational cost. - Algorithm 1: In order to solve
Problem 1, we reformulate it as a so-called assignment problem, which is a well-known problem in graph-theory. Using the digraph D (Fig. 1), we construct a graph G as shown in Fig. 4. The vertices of G can be divided into two subsets: the subset X on the left-hand side, which contains the vertices s 1 , ... ,s K-1 and K copies of s 0 , and the subset Y on the right-hand side, which contains the vertices s 1 , ... ,s K and K-1 dummy vertices, shown as †. - A number of edges connect the vertices of X and Y . Edges connected to vertices in X correspond to out-edges in the digraph D , while edges connected to vertices s 1 ,...,s K ∈ Y correspond to in-edges in D. For example, the edge from s 2 ∈ X to s 4 ∈ Y in G corresponds to the edge s 2 s 4 in the digraph D. Thus, the solid line edges in graph G represent the 'differential encoding' edges in digraph D . Furthermore, the dashed-line edges from the vertices {s 0 } ∈ X to s 1 , ... ,s K ∈ Y all correspond to direct encoding of components s 1 , ... ,s K . The weights of the edges connecting vertices in X with vertices s 1 , ... ,s K ∈ Y are identical to the weights of the corresponding edges in digraph D. Finally, the K- 1 dummy vertices {†} ∈ Y are used to represent the fact that some vertices in the solution trees may be 'leaves', i.e., do not have any out-edges. For example, in Fig. 3a, vertex s 2 is a leaf. In the graph G , this is represented as an edge from S 2 ∈ X to one of the vertices † ∈ Y . All edges connected to †-vertices have a weight of 0.
- It can be shown that each set of K edges in D that satisfies constraints a) and b) of
Problem 1, can be represented as an assignment in G of the vertices in X to the vertices in Y, i.e., a subset of 2K-1 edges in G such that each vertex is assigned exactly one edge. Figs. 5a-c show examples of assignments corresponding to the trees in Figs. 3a-c, respectively. Thus,Problem 1 can be reformulated as the so-called Assignment Problem, which we will refer to asProblem 2. - Several algorithms exist for solving
Problem 2, such as the so-called Hungarian Method, as discussed in H. W. Kuhn, "The Hungarian Method for the Assignment Problem ", Naval Research Logistics Quarterly, 2:83 - 97, 1955 which solves the problem in O((2K-1)3) arithmetic operations. An alternative implementation is an algorithm described in R. Jonker and A. Volgenant, "A Shortest Augmenting Path Algorithm for Dense and Sparse Linear Assignment Problems", Computing, vol.38, pp.325-340, 1987. The complexity is similar to the Hungarian Method, but the Jonker and Volgenants algorithm is faster in practice. Further, their algorithm can solve sparse problems faster, which is of importance for the multi-frame linking algorithm of this embodiment. - In summary,
Algorithm 1 consists of the following steps. First, the digraph D (and as a result the graph G) is constructed. Then, the assignment in G with minimal weight (Problem 2) is determined. Finally, from the assignment in G , the optimal combination of direct and differential coding is easily derived. -
Algorithm 2 is an iterative, greedy algorithm that treats the vertices s 1, ... ,s K of the graph D one at a time for increasing indices. At iteration k, one of the in-edges of vertex s k is selected from a candidate edge set. The candidate set consists of the in-edges of s k originating from vertices with no previously selected out-edge, and the direct encoding edge s 0 s k . From this set, the edge with minimal weight is selected. With this procedure, a set of K edges is obtained that satisfies constraints a) and b) ofProblem 1. Generally, this greedy approach is not optimal, i.e., there may exist another set of K edges with a lower total weight satisfying constraints a) and b).Algorithm 2 has a computational complexity of O(K 2). - In addition to the sinusoidal (delta-) parameters encoded as described above, an encoded signal embodying the invention must include side information that describes how to combine the parameters at the decoder. One possibility is to assign to each possible solution tree one symbol in the side information alphabet. However, the number of different solution trees is large; for example with K = 25 sinusoidal components in a frame, it can be shown that the number of different solution trees is approximately 1018, corresponding to 62 bits for indexing the solution tree in the side information alphabet. Clearly, this number is excessive for most applications. Fortunately, the side information alphabet only needs to represent topologically distinct solution trees, provided that a particular ordering is applied to the (delta-) parameter sequence. To clarify the notion of topologically distinct trees and parameter ordering, consider the examples of solution trees in Figs. 6a to 6c, and the corresponding parameter sequences listed below the trees. The spanning trees in Figs. 6a and 6b are topologically identical, since they each consist of a three-edge and a two-edge branch, and would thus be represented with the same symbol in the side information alphabet. Conversely, the tree in Fig. 6c, which consists of a single five-edge branch; is topologically distinct from the others. Knowing the topological tree structure and assuming for example that the (delta-) parameters occur branch-wise in the parameter stream with longest branches first, it is possible for the decoder to combine the received parameters correctly.
- Consequently, preferred embodiments of the invention provide a side information alphabet whose symbols correspond to topologically distinct solution trees. An upper bound for the side information is given by the number of such trees. There follows expressions for the number of topological distinct trees.
- As illustrated in the examples of Fig. 6a to 6c, the structure of the solution trees can be represented by specifying the length of each branch in the tree. Assuming a longest-branches-first ordering, the set of topologically distinct trees is specified by distinct sequences of non-increasing positive integers whose sum is K; in combinatorics, such sequences are referred to as "integer partitions" of the positive integer K. For example, for K = 5, there exist the following seven integer partitions: {5} (Fig. 1c), {4,1} , {3,2} (Figs. 1a and 1b), {3,1,1}, {2,2,1}, {2,1,1,1}, and {1,1,1,1,1}. Thus, for K = 5, there are seven topologically distinct solution trees, and the side information alphabet would consist of seven symbols. Letting P j (K) denote the number of integer partitions of K whose first integer is j, it is straight-forward to show that the number P of distinct solution trees is given by the following recursions:
where - Fig. 8 shows the number of topologically distinct trees as a function of the number K of sinusoidal components. Thus, indexing of the side information alphabet for K = 25 would require a maximum of 11 bits. Note that the graph represents an upper bound for the side information; exploiting statistical properties using e.g. entropy coding may reduce the side information rate further.
- The performance of the proposed algorithms can be demonstrated in a simulation study with audio signals. Four different audio signals sampled at a rate of 44.1 kHz and with a duration of approximately 20 seconds each were divided into frames of a fixed length of 1024 samples using a Hanning window with a 50% overlap between consecutive frames.
- Each signal frame was represented using a sinusoidal model with a fixed number of K=25 constant-amplitude, constant-frequency sinusoidal components, whose parameters were extracted using a matching pursuit algorithm. Amplitude and frequency parameters were quantized uniformly in the log-domain using relative quantizer level spacings of 20% and 0.5%, respectively. Similar relative quantization levels were used for direct and differential quantization, as shown in Fig. 2, and quantized parameters were encoded using Huffman coding.
- Experiments were conducted where
Algorithms - For each of these encoding procedures, the bit rate R Pars , needed for encoding of (delta-) amplitudes and frequencies was estimated (using first-order entropies). Furthermore, since
Algorithms - The columns in Table 1 below show bit rates [kbps] for various coding schemes and test signals. The table columns are R Pars : bit rate for representing (delta-) amplitudes and frequencies, R S.I : rate needed for side information (tree structures), and R Total : total rate. Gain is the relative improvement with various FD encoding schemes over direct encoding (non-differential).
- Table 1 shows that using
Algorithm 1 for determining the combination of direct and FD encoding gives a bit-rate reduction in the range of 18.8-27.0% relative to direct encoding.Algorithm 2 performs nearly as well with bit-rate reductions in the range of 18.5-26.7%. The slightly lower side information resulting fromAlgorithm 2 is due to the fact thatAlgorithm 2 tends to produce solution trees with fewer but longer 'branches', thereby reducing the number of different solution trees observed. Finally, the 'standard' method of FD encoding reduces the bit rate with 12.7-24.0%. - Therefore, encoding methods are provided that use two algorithms for determining the bit-rate optimal combination of direct and FD encoding of sinusoidal components in a given frame. In simulation experiments with audio signals, the presented algorithms showed bit-rate reductions of up to 27% relative to direct encoding. Furthermore, the proposed methods reduced the bit rate with up to 7% compared to a typically used FD encoding scheme. While consideration of the invention has been focussed on FD encoding as a stand-alone technique, in further embodiments the scheme is generalizes to describe FD encoding in combination with TD encoding. With such joint TD/FD encoding schemes, it is possible to provide embodiments that combine the strengths of the two encoding techniques.
- It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design many alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word 'comprising' does not exclude the presence of other elements or steps than those listed in a claim. The invention can be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In a device claim enumerating several means, several of these means can be embodied by one and the same item of hardware. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.
Table 1 Signal 1 R Pars . R S.I R Total Gain Direct 29.1 0 29.1 - Alg.1 20.8 0.6 21.4 26.5% Alg.2 20.9 0.5 21.5 26.1% Standard 22.3 0 22.3 23.4% Signal 2 R Pars. R S.I R Total Gain Direct 27.6 0 27.6 - Alg.1 21.6 0.7 22.4 18.8% Alg. 2 21.8 0.7 22.5 18.5% Standard 24.1 0 24.1 12.7% Signal 3 R Pars. R S.I R Total Gain Direct 30.0 0 30.0 - Alg.1 21.2 0.7 21.9 27.0% Alg. 2 21.4 0.6 22.0 26.7% Standard 22.8 0 22.8 24.0% Signal 4 R Pars R S.I R Total Gain Direct 28.6 0 28.6 - Alg. 1 21.5 0.7 22.2 22.4% Alg. 2 21.8 0.7 22.5 21.3% Standard 22.9 0 22.9 19.9%
Claims (17)
- A method of coding an audio signal, the method being characterised by a step of algorithmically determining whether each parameter of a given sinusoidal component in encoded frames is to be encoded differentially or directly, and a step of encoding each parameter either differentially relative to other components in the same frame or directly, i.e. without differential encoding in accordance with the determination.
- A method according to claim 1 in which the algorithm includes the steps of:a. constructing a digraph D of the set of all possible combinations of direct and differential quantized components and from that, constructing a graph G;b. determining the assignment in G with minimal total weight; andc. deriving the optimal combination of direct and differential coding from the assignment in G.
- A method according to claim 1 in which the algorithm makes an approximate determination as to whether a parameter is encoded in differentially or directly.
- A method according to claim 1 or claim 3 in which the algorithm is an iterative, greedy algorithm.
- A method according to claim 4 in which the algorithm includes steps of:a. constructing a digraph D of the set of all possible combinations of direct and differential quantized components;b. treating the vertices s 1 , ... ,s K of the graph D one at a time for increasing indices;c. at iteration k, one of the in-edges of vertex s k is selected from a candidate edge set, the candidate edge set comprising the in-edges of s k originating from vertices with no previously selected out-edge, and the direct encoding edge s 0 s k ; andd. selecting from this set, the edge with minimal weight.
- A method according to claim 2 including a step of finding an optimal combination in graph G of the set of 2K-1 edges with minimum total weight such that each vertex is assigned exactly one edge.
- A method according to claim 6 in which the set of edges with minimum weight is found by a procedure that includes use of the Hungarian Method for solving the assignment problem.
- A method according to claim 6 in which the set of edges with minimum weight is found by a procedure that includes use of a shortest augmenting path algorithm for solving the assignment problem.
- A method according to any preceding claim further comprising a step of generating side information that specifies whether components in a frame are encoded differentially or directly.
- An encoding device for coding an audio signal, the encoding device comprising means for encoding parameters of a given sinusoidal component characterised in that the encoding device comprises means to determine algorithmically whether each parameter of a given sinusoidal component in encoded frames is to be encoded differentially or directly, and means for encoding parameters in encoded frames either differentially relative to other components in the same frame or directly, i.e. without differential encoding in accordance with the determination.
- A method of decoding an encoded audio signal, which encoded audio signal comprises parameters of a given sinusoidal component characterised in that the parameters have been encoded in encoded frames either differentially relative to other components in the same frame or directly, i.e. without differential encoding, wherein the method comprises interpreting the signal to determine whether a component in a frame is to be decoded differentially or directly and decoding the component in accordance with the result of the determination.
- A method of decoding an encoded audio signal according to claim 11 in which the signal has been encoded in accordance with a method of any one of claims 1 to 9.
- A device for decoding an encoded audio signal, which encoded audio signal comprises parameters of a given sinusoidal component which have been encoded in encoded frames either differentially relative to other components in the same frame or directly, i.e. without differential encoding, said device comprising determination means to determine whether a component in a frame is to be decoded differentially or directly and decoding means adapted to operate in accordance with said determination.
- An encoded audio signal that comprises parameters of a given sinusoidal component which have been encoded in encoded frames either differentially relative to other components in the same frame or directly, i.e. without differential encoding, in which the signal includes side information that specifies whether components in a frame are encoded differentially or directly.
- A storage medium on which an encoded audio signal as claimed in claim 14 has been stored.
- An apparatus for transmitting or recording an encoded audio signal, the apparatus comprising:a. an input unit for obtaining an audio signal,b. a device according to claim 10 for coding the audio signal to obtain the encoded audio signal, andc. an output unit for transmitting or recording the encoded audio signal.
- An apparatus for receiving and/or reproducing an encoded audio signal, the apparatus comprising:a. an input unit for receiving the encoded audio signal,b. a device according to claim 13 for decoding the encoded audio signal to obtain a decoded audio signal, andc. an output unit for outputting the decoded audio signal.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
EP02762729A EP1442453B1 (en) | 2001-10-19 | 2002-09-27 | Frequency-differential encoding of sinusoidal model parameters |
Applications Claiming Priority (6)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
EP01203934 | 2001-10-19 | ||
EP01203934 | 2001-10-19 | ||
EP02077844 | 2002-07-15 | ||
EP02077844 | 2002-07-15 | ||
PCT/IB2002/004018 WO2003036619A1 (en) | 2001-10-19 | 2002-09-27 | Frequency-differential encoding of sinusoidal model parameters |
EP02762729A EP1442453B1 (en) | 2001-10-19 | 2002-09-27 | Frequency-differential encoding of sinusoidal model parameters |
Publications (2)
Publication Number | Publication Date |
---|---|
EP1442453A1 EP1442453A1 (en) | 2004-08-04 |
EP1442453B1 true EP1442453B1 (en) | 2006-09-06 |
Family
ID=26077015
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP02762729A Expired - Lifetime EP1442453B1 (en) | 2001-10-19 | 2002-09-27 | Frequency-differential encoding of sinusoidal model parameters |
Country Status (8)
Country | Link |
---|---|
US (1) | US7269549B2 (en) |
EP (1) | EP1442453B1 (en) |
JP (1) | JP2005506581A (en) |
KR (1) | KR20040055788A (en) |
CN (1) | CN1312659C (en) |
AT (1) | ATE338999T1 (en) |
DE (1) | DE60214584T2 (en) |
WO (1) | WO2003036619A1 (en) |
Families Citing this family (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
BRPI0304542B1 (en) * | 2002-04-22 | 2018-05-08 | Koninklijke Philips Nv | “Method and encoder for encoding a multichannel audio signal, encoded multichannel audio signal, and method and decoder for decoding an encoded multichannel audio signal” |
KR101287528B1 (en) | 2006-09-19 | 2013-07-19 | 삼성전자주식회사 | Job Assignment Apparatus Of Automatic Material Handling System And Method Thereof |
KR101317269B1 (en) | 2007-06-07 | 2013-10-14 | 삼성전자주식회사 | Method and apparatus for sinusoidal audio coding, and method and apparatus for sinusoidal audio decoding |
KR20090008611A (en) * | 2007-07-18 | 2009-01-22 | 삼성전자주식회사 | Audio signal encoding method and appartus therefor |
KR101346771B1 (en) | 2007-08-16 | 2013-12-31 | 삼성전자주식회사 | Method and apparatus for efficiently encoding sinusoid less than masking value according to psychoacoustic model, and method and apparatus for decoding the encoded sinusoid |
KR101410230B1 (en) | 2007-08-17 | 2014-06-20 | 삼성전자주식회사 | Audio encoding method and apparatus, and audio decoding method and apparatus, processing death sinusoid and general continuation sinusoid in different way |
KR101425354B1 (en) * | 2007-08-28 | 2014-08-06 | 삼성전자주식회사 | Method and apparatus for encoding continuation sinusoid signal of audio signal, and decoding method and apparatus thereof |
KR101380170B1 (en) * | 2007-08-31 | 2014-04-02 | 삼성전자주식회사 | A method for encoding/decoding a media signal and an apparatus thereof |
EP3714771A1 (en) | 2008-10-01 | 2020-09-30 | Inspire Medical Systems, Inc. | System for treating sleep apnea transvenously |
US20110153337A1 (en) * | 2009-12-17 | 2011-06-23 | Electronics And Telecommunications Research Institute | Encoding apparatus and method and decoding apparatus and method of audio/voice signal processing apparatus |
US8489403B1 (en) * | 2010-08-25 | 2013-07-16 | Foundation For Research and Technology—Institute of Computer Science ‘FORTH-ICS’ | Apparatuses, methods and systems for sparse sinusoidal audio processing and transmission |
PL232466B1 (en) | 2015-01-19 | 2019-06-28 | Zylia Spolka Z Ograniczona Odpowiedzialnoscia | Method for coding, method for decoding, coder and decoder of audio signal |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CA2140779C (en) * | 1993-05-31 | 2005-09-20 | Kyoya Tsutsui | Method, apparatus and recording medium for coding of separated tone and noise characteristics spectral components of an acoustic signal |
CN1099777C (en) * | 1993-06-30 | 2003-01-22 | 索尼公司 | Digital signal encoding device, its decoding device, and its recording medium |
BE1007617A3 (en) * | 1993-10-11 | 1995-08-22 | Philips Electronics Nv | Transmission system using different codeerprincipes. |
WO1999062189A2 (en) * | 1998-05-27 | 1999-12-02 | Microsoft Corporation | System and method for masking quantization noise of audio signals |
US6510407B1 (en) * | 1999-10-19 | 2003-01-21 | Atmel Corporation | Method and apparatus for variable rate coding of speech |
-
2002
- 2002-09-27 AT AT02762729T patent/ATE338999T1/en not_active IP Right Cessation
- 2002-09-27 KR KR10-2004-7005778A patent/KR20040055788A/en not_active Application Discontinuation
- 2002-09-27 DE DE60214584T patent/DE60214584T2/en not_active Expired - Fee Related
- 2002-09-27 CN CNB028207076A patent/CN1312659C/en not_active Expired - Fee Related
- 2002-09-27 WO PCT/IB2002/004018 patent/WO2003036619A1/en active IP Right Grant
- 2002-09-27 JP JP2003539025A patent/JP2005506581A/en not_active Withdrawn
- 2002-09-27 EP EP02762729A patent/EP1442453B1/en not_active Expired - Lifetime
- 2002-10-14 US US10/270,948 patent/US7269549B2/en not_active Expired - Fee Related
Also Published As
Publication number | Publication date |
---|---|
CN1312659C (en) | 2007-04-25 |
DE60214584T2 (en) | 2007-09-06 |
CN1571992A (en) | 2005-01-26 |
KR20040055788A (en) | 2004-06-26 |
EP1442453A1 (en) | 2004-08-04 |
DE60214584D1 (en) | 2006-10-19 |
US7269549B2 (en) | 2007-09-11 |
US20040204936A1 (en) | 2004-10-14 |
WO2003036619A1 (en) | 2003-05-01 |
ATE338999T1 (en) | 2006-09-15 |
JP2005506581A (en) | 2005-03-03 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
KR101058062B1 (en) | Improving Decoded Audio Quality by Adding Noise | |
US5371853A (en) | Method and system for CELP speech coding and codebook for use therewith | |
KR101278805B1 (en) | Selectively using multiple entropy models in adaptive coding and decoding | |
JP3203657B2 (en) | Information encoding method and apparatus, information decoding method and apparatus, information transmission method, and information recording medium | |
EP1442453B1 (en) | Frequency-differential encoding of sinusoidal model parameters | |
WO1995001680A1 (en) | Digital signal encoding device, its decoding device, and its recording medium | |
JP2003323198A (en) | Encoding method and device, decoding method and device, and program and recording medium | |
JP4622164B2 (en) | Acoustic signal encoding method and apparatus | |
KR100968057B1 (en) | Encoding method and device, and decoding method and device | |
US7363216B2 (en) | Method and system for parametric characterization of transient audio signals | |
JP2007504503A (en) | Low bit rate audio encoding | |
Ozkan et al. | Secure voice communication via GSM network | |
KR100952065B1 (en) | Coding method, apparatus, decoding method, and apparatus | |
JP3475985B2 (en) | Information encoding apparatus and method, information decoding apparatus and method | |
Najih et al. | Comparing speech compression using wavelets with other speech compression schemes | |
Jensen et al. | Schemes for optimal frequency-differential encoding of sinusoidal model parameters | |
Jensen et al. | Optimal frequency-differential encoding of sinusoidal model parameters | |
JP5544371B2 (en) | Encoding device, decoding device and methods thereof | |
JP2002374171A (en) | Encoding device and method, decoding device and method, recording medium and program | |
Jensen et al. | Time-differential encoding of sinusoidal model parameters for multiple successive segments | |
Ghahabi et al. | A fast, efficient and scalable algorithm for perceptual high quality speech coding | |
Anandakumar et al. | Self-affine modeling of speech signal in speech compression | |
Kaouri et al. | High quality low bit rate transform sub-band coding of speech | |
JP2002368622A (en) | Encoder and encoding method, decoder and decoding method, recording medium, and program | |
JP2002359560A (en) | Coder and coding method, decoder and decoding method, recording medium and program |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PUAI | Public reference made under article 153(3) epc to a published international application that has entered the european phase |
Free format text: ORIGINAL CODE: 0009012 |
|
17P | Request for examination filed |
Effective date: 20040519 |
|
AK | Designated contracting states |
Kind code of ref document: A1 Designated state(s): AT BE BG CH CY CZ DE DK EE ES FI FR GB GR IE IT LI LU MC NL PT SE SK TR |
|
GRAP | Despatch of communication of intention to grant a patent |
Free format text: ORIGINAL CODE: EPIDOSNIGR1 |
|
GRAS | Grant fee paid |
Free format text: ORIGINAL CODE: EPIDOSNIGR3 |
|
GRAA | (expected) grant |
Free format text: ORIGINAL CODE: 0009210 |
|
AK | Designated contracting states |
Kind code of ref document: B1 Designated state(s): AT BE BG CH CY CZ DE DK EE ES FI FR GB GR IE IT LI LU MC NL PT SE SK TR |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: SK Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20060906 Ref country code: NL Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20060906 Ref country code: FI Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20060906 Ref country code: CZ Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20060906 Ref country code: CH Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20060906 Ref country code: BE Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20060906 Ref country code: IT Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT;WARNING: LAPSES OF ITALIAN PATENTS WITH EFFECTIVE DATE BEFORE 2007 MAY HAVE OCCURRED AT ANY TIME BEFORE 2007. THE CORRECT EFFECTIVE DATE MAY BE DIFFERENT FROM THE ONE RECORDED. Effective date: 20060906 Ref country code: AT Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20060906 Ref country code: LI Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20060906 |
|
REG | Reference to a national code |
Ref country code: GB Ref legal event code: FG4D |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: IE Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20060927 |
|
REG | Reference to a national code |
Ref country code: CH Ref legal event code: EP |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: MC Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20060930 |
|
PGFP | Annual fee paid to national office [announced via postgrant information from national office to epo] |
Ref country code: GB Payment date: 20061003 Year of fee payment: 5 |
|
REG | Reference to a national code |
Ref country code: IE Ref legal event code: FG4D |
|
REF | Corresponds to: |
Ref document number: 60214584 Country of ref document: DE Date of ref document: 20061019 Kind code of ref document: P |
|
PGFP | Annual fee paid to national office [announced via postgrant information from national office to epo] |
Ref country code: DE Payment date: 20061110 Year of fee payment: 5 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: SE Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20061206 Ref country code: DK Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20061206 Ref country code: BG Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20061206 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: ES Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20061217 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: PT Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20070219 |
|
NLV1 | Nl: lapsed or annulled due to failure to fulfill the requirements of art. 29p and 29m of the patents act | ||
REG | Reference to a national code |
Ref country code: CH Ref legal event code: PL |
|
ET | Fr: translation filed | ||
PLBE | No opposition filed within time limit |
Free format text: ORIGINAL CODE: 0009261 |
|
STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: NO OPPOSITION FILED WITHIN TIME LIMIT |
|
26N | No opposition filed |
Effective date: 20070607 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: GR Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20061207 |
|
GBPC | Gb: european patent ceased through non-payment of renewal fee |
Effective date: 20070927 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: EE Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20060906 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: DE Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20080401 Ref country code: LU Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20060927 Ref country code: TR Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20060906 |
|
REG | Reference to a national code |
Ref country code: FR Ref legal event code: ST Effective date: 20080531 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: FR Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20071001 |
|
PGFP | Annual fee paid to national office [announced via postgrant information from national office to epo] |
Ref country code: FR Payment date: 20061023 Year of fee payment: 5 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: CY Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20060906 Ref country code: GB Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20070927 |